What the data for this category looks like
The data for iron ore intelligent due diligence reports comes from three primary sources: Dalian Commodity Exchange delivery standard data, domestic major port spot trading platforms, and international mining monthly shipping announcements. Data update frequencies differ:
- Port spot data updates daily
- Futures delivery product data updates with each trading day
- Mine direct shipping production data updates weekly
The document structure is a structured table with fields including batch number, origin, total iron content, impurity content, particle size distribution, loading and unloading port, quotation, and inventory quantity. Inventory is measured in wet tons. Total iron content is based on dry basis, with no percentage notation used.
Constraints Imposed on HTTP Interfaces and External Systems
Differences between multi-source data sources require interfaces to support configuring multiple external data source endpoints and adapting to authentication rules for each data source. Differing update frequencies require interfaces to allow separate pull interval configurations per data source, preventing frequent pulls of outdated data or missed real-time updates. Unique iron ore fields and units require interfaces to return standardized fields with accompanying unit descriptions, avoiding parsing errors in external systems due to unit mismatches. Precise batch-based query needs require interfaces to support filtering by batch number, origin, and loading/unloading port, to meet customized query requirements for due diligence reports.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
external_data_source_type | structured_api | Matches the interface format of iron ore structured data, no additional unstructured parsing required |
update_interval | 3600 seconds | Adapts to the daily update frequency of port spot data, covers regular update rhythms during trading days and non-trading days |
field_mapping_rules | {"全铁含量":"tfe_content", "湿吨库存":"wet_ton_stock"} | Standardizes the mapping between iron ore unique fields and external system parameters, avoiding unit ambiguity |
api_timeout | 120 seconds | Adapts to the time consumption requirements of multi-source data pulling, preventing timeouts caused by data volume fluctuations |
batch_query_enabled | true | Supports filtering queries by batch number and origin, matching the batch dimension requirements of due diligence reports |
max_batch_size | 50 entries | Adapts to the upper limit of data volume for single-batch due diligence reports, preventing interface return overload |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three Common Configuration Mistakes
- Duplicate iron ore batch data is returned by the interface. The symptom is multiple records with the same batch number appearing in the response. The cause is that deduplication rules for multi-source data have not been configured, and different data sources pull duplicate information for the same batch.
- The interface call returns a
400 Bad Requesterror. The symptom is parameter verification failure. The cause is that parameters are not passed in accordance with the unit requirements of iron ore unique fields, and non-standard units are misused leading to format mismatch. - No valid data is returned after a scheduled pull task is triggered. The symptom is that core fields such as total iron content and inventory are missing from the response. The cause is that corresponding authentication parameters have not been configured for different data sources, resulting in failure to normally obtain authorized data.
How to Verify Successful Configuration
- Call the configured interface, pass a known iron ore batch number, and check if the returned fields include core indicators such as total iron content, inventory, and origin.
- View the interface authentication log to confirm that the request carries correct authentication parameters, with no authentication failure records.
- Simulate a scheduled pull task, and check if the update timestamp of the returned results aligns with the official update time of the data source.
- Call the batch query interface, pass multiple origin parameters, and check if the returned results correctly filter iron ore data for the corresponding origins.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.